The rapid development of artificial intelligence technologies and their widespread implementation across various spheres of human activity highlight the urgent need for mass education in AI tool usage, particularly in mastering prompt engineering techniques. Traditional educational approaches cannot keep pace with technological change, creating a gap between labor market demands and competencies of educational programs’ graduates. Purpose. To present the architecture and design methodology of an interactive simulator system with automated assessment based on large language models for teaching various aspects of working with AI tools; to describe the practical implementation experience in development courses. Methodology and research methods. The study is based on instructional design methodology and gamification theory in education. The system architecture is implemented using client-side web technologies (HTML5, JavaScript) and integration with the API of large language models (OpenRouter) for automated assessment of open-ended tasks. Approbation was carried out in the context of advanced training courses under the program “Introduction to neural networks: practical development of AI platforms”. Results and scientific novelty. An interactive simulator system architecture was developed, including six specialized modules: prompt engineering techniques (Zero-shot, Few-shot, Chain-of-Thought, etc.), AI ethics, image and video generation, presentation creation, and AI data analytics. Scientific novelty lies in applying large language models for automated assessment of creative assignments with detailed feedback generation without instructor involvement. The system integrates gamification mechanisms (achievement system, progressive content unlocking) to enhance learner motivation. Practical significance. The presented system can be integrated into teacher professional development courses and higher education programs in various subject areas. The modular architecture provides the ability to adapt simulators to different subject areas and educational contexts. Areas for further development of the system have been identified, including integration with LMS through SCORM packages and the development of its own plugin for educational analytics.

The purpose of the study. The digitalization of education implies large-scale transformations encompassing the implementation of digital technologies at every level of general and vocational education, as well as additional education, as well as changes in the interactions of all participants in the educational process. One of the six key challenges addressed by the Education Development Strategy to 2036 is the rapid spread of digital technologies and artificial intelligence. The aim of this study is to determine the role of digital traces generated during the educational process as a tool for digital transformation in educational management, as well as to demonstrate the practical implementation of digital trace processing using the VKontakte social network API and data analysis methods (Educational Data Mining). Materials and Methods . The theoretical and methodological basis for the study was formed by the work of Russian and international researchers in the field of digital data analysis arising during the educational process. The study utilized data analysis methods, natural language processing techniques, and Python libraries such as pandas, numpy, mathplotlib, and others. The empirical portion of the study is based on the analysis of the digital footprint of the educational organization's communities on the social network VKontakte, represented as unstructured text. Results . Research shows that large volumes of heterogeneous digital trace data, including those presented in the form of semi-structured data, inevitably arise in the context of the digitalization of education and ensuring the information openness of educational organizations. This data is of interest for educational analytics used to address issues related to the digital transformation of the educational process, the digital transformation of educational management, and the continuity and integration of educational levels. The digital trace generated through interactions with the electronic information and educational environment and other digital resources of educational organizations on the internet (websites, social media pages, and instant messaging apps) opens up opportunities for analyzing data on the educational process and participants in educational relationships. However, systematic approaches to its analysis and use in the context of the digital transformation of education are required, including those that take into account legal requirements for personal data, ethical aspects, and security aspects. This article examines the prospects for analyzing digital data in educational organization communities on social media using data analysis and machine learning methods and presents a practical example of data analysis in such communities on the social network VKontakte using an API. Conclusion . The obtained results can be used both for initial studies of digital footprint analysis and as a basis for developing a system for generating educational analytics. Practical application of the results will facilitate the digital transformation of educational management.

The aim of the paper is to conduct a comprehensive analysis and systematization of the legal and regulatory framework governing the development of digital literacy among future foreign language teachers, identify key contradictions and deficiencies in its content, and provide a theoretical justification and develop a concept of professional digital literacy for foreign language teachers, correlated with current strategic documents, professional standards, and educational standards, and focused on the subsequent design of educational programs and modules for the development of digital competencies. The study clarifies the content of the concept of “professional digital literacy of foreign language teachers” and its connection with the requirements of current strategic documents, professional standards, and educational standards of higher education. Materials and methods: the study used a systematic analysis of current legal and regulatory documents in the field of education, including the Federal law “On Education in the Russian Federation”, the professional standard “Teacher,” the Federal state educational standard of higher education in the field of training 44.03.05 “Pedagogical education,” as well as national projects and strategies for digital development. Methods of comparative analysis, content analysis of scientific publications, synthesis, and systematization of the data obtained were used. The empirical base consisted of twenty-four sources, including scientific articles, monographs, and legal regulatory acts, selected according to criteria of relevance to the topic of digital literacy of teachers and the specifics of training foreign language teachers. Results: a multi-level system of legal and regulatory support for teachers’ digital literacy has been identified, including strategic documents (the national projects “Data economy and digital transformation of the state” and “Education”), sectoral standards (the Federal state educational standard of higher education and the professional standard for teachers) and departmental regulations. It is shown that existing regulatory requirements, while providing a general framework for the digital transformation of education, only partially consider the specifics of the professional activities of a foreign language teacher, associated with the intensive use of digital language resources, online platforms and artificial intelligence tools. Key contradictions have been identified between the dynamic development of digital technologies and the relatively static character of the regulatory framework, as well as between the integral nature of professional digital literacy and the fragmentarity of its normative consolidation in different documents. Conclusion: a concept of professional digital literacy for foreign language teachers has been developed, including linguo-didactic, technological, communicative, and ethical-legal components. The following areas for improving the legal and regulatory framework have been proposed: the development of industry recommendations on digital literacy for foreign language teachers, the creation of a system for the continuous development of digital competencies at the stages of basic training and professional development, and the integration of requirements for working with artificial intelligence and large language models into educational standards and model basic professional educational programs. The practical significance of the results lies in the possibility of using the developed concept and proposed directions when updating curricula, forming modules on digital literacy in pedagogical universities, and designing programs for additional professional education.

The purpose of the research. Development of a set of business requirements for the software of digital educational platforms, intended for the formation and implementation of networked educational programs in continuing professional education. Research methods. The study employed methods of comparative analysis and decomposition. Analysis of the regulatory framework and scientific literature resulted in the identification of key characteristics of the network form of educational program implementation. A comparative analysis of seven russian-developed educational platforms was conducted to assess their support for these characteristics. Based on the identified limitations of existing solutions, a set of business requirements was formulated. Results. Five key characteristics of the network form of educational program implementation were identified (shared resource pool, heterogeneous modules, flexible organizational structure, integration with the labor market, personalized learning), distinguishing it from traditional models of network education organization. The comparative analysis revealed incomplete support for these characteristics by modern platforms, particularly regarding the flexible organization structure. Based on these characteristics, a set of five business requirements (business requirements - 1 – business requirements - 5) for the architecture of network digital educational platforms was formulated, aimed at ensuring horizontal network interaction, modular program assembly, and dynamic adaptation of educational trajectories. Conclusion. The developed set of business requirements provides a methodological foundation for designing a new class of information systems – network digital educational platforms – that overcome the technological gap between existing solutions and the needs of networked continuing professional education organization. The requirements have an engineering nature and can be used for drafting technical specifications when creating specific platforms that realize the advantages of network form of educational program implementation.

The purpose of the study is to develop methods for optimal estimation of unknown non-random factors affecting the quality of production equipment by the criterion of maximum likelihood, as well as random factors by the criterion of minimum standard error based on the processing of information related to claims received using the mathematical theory of random point processes and the theory of statistical solutions. The research method consists in applying the well-known hypothesis about the distribution of operating time for failure of technical systems in the form of an exponential distribution depending on the failure rate function. The fact is used that the corresponding distribution of the number of failures is distributed according to the Poisson law with the same function of failure rates. It is assumed that the intensity function depends not only on time, but also on a set of unknown non-random parameters, or on random parameters. It is emphasized that such factors may reflect the generalized state of the technical system, and information about this may be contained in the facts of product claims. The task of optimal estimation of the parameters on which the failure rate function depends is set. Since in this formulation of the problem, only the facts of filing claims, as well as the times of their presentation, are available for processing, the maximum likelihood function method is used for optimal estimation of nonrandom parameters, and the optimal Kalman filter is used for random parameters. The problem of optimal estimation of unknown parameters from a multiplicatively separable failure rate function, i.e. one that is representable as a product of a separate function of time and a vector function of unknown parameters, is considered. It is shown that for such a function, the optimal estimation problem is reduced to the problem of estimating a single scalar parameter that scales the time function. The well-known Kalman algorithm for continuous parameters is applied to the case of the observed process in the form of the number of claims’ events and the time of their occurrence. Examples of evaluation of both unknown and random factors are given for unified real data on tissue defects, and confirm the operability of the algorithms and their applicability for the simplest assessments of the condition of production equipment. The new results include the formulation of the problem of studying a failure intensity function that depends on a set of unknown nonrandom parameters, the application of the maximum likelihood method and Kalman algorithm for optimal estimation of these parameters, and the proof that for a separable failure intensity function, the optimal estimation reduces to the estimation of a scalar quantity that scales the time-dependent intensity function. The conclusion states that examples of assessment of factors affecting the function of the failure rate confirm the operability of the algorithm and its applicability for the simplest assessments of the condition of production equipment. A separate task is to develop analytical expressions for the failure rate function that depends on parameters, as well as methods for comparing estimates obtained by different methods. Solving these tasks will make it possible to develop methods for clarifying the condition of production equipment.

Purpose of the research. To conduct a meta-analysis to identify and systematize the relationships between key teachers’ personnel characteristics (professional competence, motivation, psychological climate, participation in further professional education, and others) and academic results of students. Materials and methods. The meta-analysis included 35 scientific articles published between 2019 and 2025, selected from Russian and international electronic bibliometric databases. The selection criteria were relevance to the topic, the presence of an empirical sample, and quantitative results. We used content analysis and comparative analysis methods to systematize the data, summarizing the findings in thematic summary tables. Results. The analysis established that the greatest influence on student academic achievement comes from a teacher’s professional competence (high correlations r = 0.675 – 0.89), their intrinsic motivation and job satisfaction (β = 0.34 –12.56; r = 0.88 – 0.94), and the quality of the teacher-student relationship (moderate to high correlations r = 0.41 – 0.725). Systematic further professional education shows a consistent positive association with academic performance (r = 0.678; β = 0.31). The influence of factors such as gender matching, salary, and length of service proved weak or statistically insignificant and highly context-dependent. Conclusion. The meta-analysis results confirm that educational effectiveness is largely determined by a complex of a teacher’s psychological, pedagogical, and personal characteristics, rather than by their formal parameters alone. The most effective directions for educational policy are investing in competence development, supporting motivation and a positive psychological climate, and creating systems for teachers’ continuous professional development.

Purpose of the study. This article aims to identify and systematically analyze the dual effects and risks associated with the use of generative artificial intelligence (GenAI) in higher education, with a specific focus on its impact on students’ metacognitive skills. The study seeks to define the pedagogical conditions under which GenAI functions not as a replacement for cognitive engagement, but as a purposeful instrument for supporting metacognitive regulation – encompassing its three core components: planning, monitoring, and evaluation of one’s own learning. Materials and methods. The study is grounded in a systematic review of empirical research published between 2023 and 2025, including both quantitative and qualitative studies from the fields of pedagogy, cognitive psychology, and educational technologies. Theoretical generalization, synthesis, and structural analysis of scholarly literature were employed in the paper. The theoretical framework draws on J. Flavell’s model of metacognitive regulation and G. Zimmerman’s theory of self-regulated learning, further enriched by insights from distributed cognition theory. Results. The analysis revealed a fundamental duality in GenAI’s influence: on the one hand, it can foster metacognitive development through structured support, socratical interaction, and reflective dialogue; on the other hand, it can provoke such negative phenomena as “metacognitive laziness,” false self-efficacy, and cognitive passivity. Based on the conducted synthesis, an analytical framework is proposed that includes four key conditions for the effective integration of GenAI: (1) explicit definition of the AI’s functional role (coach, opponent, mentor, facilitator, etc.); (2) linking interaction to a specific component of metacognitive regulation; (3) a mandatory reflective component; and (4) teaching prompt engineering as a metacognitive skill. A typology of possible pedagogical strategies is developed, differentiated by three components of regulation: (1) planning – AI as a training coach; (2) monitoring – AI as a “mirror of understanding” or a tool for comparative analysis; and (3) evaluation – AI as a counterargument generator or a facilitator of meta-discussion. Conclusion. Generative AI itself does not carry an unequivocal risk or benefit for metacognitive development; its effect is determined solely by the pedagogical context of integration. The crucial condition for productive use is a reconceptualization of AI’s role – not as a tool for automating thought, but as a dynamic learning partner. The author advocates for cultivating an experimental, reflective, and dialogic culture of GenAI implementation, one centered on preserving and strengthening students’ cognitive autonomy as a foundational goal of contemporary higher education. This approach entails more than mere technical proficiency with AI; it requires fostering students’ critical awareness, readiness for meta-level analysis of their own cognitive strategies, and a sense of responsibility for their learning process.

Purpose of the research. The rapid digital transformation of higher medical education is leading to a rethinking of traditional pedagogical approaches, necessitating a search for more flexible and accessible teaching tools. In this context, FOAMed (Free Open Access Medical Education), an international movement promoting free and open medical education, has gained popularity. This literature review aims to analyze existing modalities used within FOAMed, including podcasts, video content, social media, and blogs. Furthermore, an analysis of their educational potential was conducted. Materials and methods. For the information search, we used PubMed, the largest international database of scientific publications. Articles were searched using the keywords “FOAMed”, “Medical Education”, “Digital pedagogy”, “Podcast”, “Vodcast”, “Social media”, and “Free Open Access Medical Education”. The search was focused on publications dedicated to the education of medical students, interns, practicing physicians, and mid-level medical professionals. 864 scientific publications from the past 10 years were identified, 32 of which were used in this literature review because they were available in full text and met the objectives of this review. Results. The review shows that FOAMed encompasses a variety of educational modalities – podcasts, video content, social media, and blogs – each with its own pedagogical advantages and potential limitations. These formats not only complement traditional education but also create a new educational environment where activity, motivation, and knowledge accessibility play a key role. FOAMed is particularly significant in the context of the media activity of the Faculty of higher medical education. This opens up opportunities for expanding educational influence, shaping professional image, developing pedagogical innovations, and creating global networking. The lecturer becomes not just knowledge holder but also an active participant in the digital educational field, capable of creating, disseminating, and interpreting knowledge within the modern media paradigm. Conclusion. FOAMed has the potential to become an important component of the teaching activities and educational strategy of the medical university, especially in the context of hybrid and distance learning. Potential for incorporating FOAMed into official educational programs and areas for further research were also identified.

This article systematically examines the problem of implementing digital educational technologies in primary schools, focusing on identifying key factors of effectiveness, barriers, and pedagogical practices that determine the quality of digital integration into the educational process for young school students. The purpose of the study is to provide a comprehensive picture of the current practice of implementing digital educational technologies, assess the impact of infrastructural and methodological factors, and develop recommendations and a phased implementation model that takes into account the age and psychological characteristics of pupils in grades 1–4. The study was conducted using mixed-methods. The quantitative component included a survey of 48 primary school teachers and 210 parents, as well as an analysis of lesson logs from 32 lessons conducted in 12 schools with varying levels of technical equipment (urban and rural schools). The qualitative component included 12 semi-structured interviews with principals and methodologists, as well as a thematic analysis of field notes and transcripts. Descriptive statistics, χ² – association tests, and correlation methods were used for quantitative data processing; for qualitative data, a stepwise thematic analysis with cross-validated coding was used. The study results showed that technical equipment (interactive whiteboards, tablets, and centralized access to educational platforms) significantly increases the likelihood of teachers regularly using digital educational technologies. However, technology alone does not ensure pedagogical quality: key determinants of effective integration include teachers’ methodological training, the availability of adapted lesson plans, and an organized system of technical support. Practical observations revealed an increase in school students’ engagement when using visualization and interactive elements; however, the acceleration of exercises with digital simulators was not always accompanied by a deep understanding of the material without stages of reflection and comprehension. The practical significance of this paper lies in the specific tools to support teachers and school principals in the transition to meaningful digitalization of primary education. To confirm the dynamic impact of digital educational technologies on academic achievement, the authors recommend conducting longitudinal and quasi-experimental studies, as well as assessing the cost-effectiveness of investments in infrastructure and teacher professional development.

The purpose of the study . In the context of the dynamic development of technologies and the tightening of requirements for industrial safety in the gas industry, the system of continuous training and professional development of personnel is of particular importance. The training and production centers of companies such as LLC “Gazprom Transgaz Kazan” are a key link in providing enterprises with highly qualified personnel. However, their effectiveness directly depends on their ability to adapt to modern challenges, including digitalization, cost optimization, and increased flexibility in the educational process.The purpose of the study is to conduct a comprehensive analysis of the current state of educational activities of the training and production centers of LLC “Gazprom Transgaz Kazan” and to develop a scientifically based action plan for its modernization aimed at improving the quality of education, reducing costs and introducing advanced educational technologies. Materials and methods . The study is based on data from the internal reporting of the training and production centers for 2021-2025. Methods of comparative analysis, expert assessment of the material and technical base, educational and methodological support and personnel potential of the center were used. Results . A set of measures for the digital transformation of the educational process is proposed as the main vector of modernization. For the practical implementation of the proposals, a detailed roadmap has been developed for the period up to 2027, structured in five stages with an assessment of risks and deadlines. The expected result of the implementation is the creation of a flexible, technologically advanced and cost-effective educational environment that meets the company’s strategic goals in the field of quality and industrial safety. Conclusion . With the implementation of the proposed measures, it is expected to increase the effectiveness of educational activities and improve the quality of professional training of employees.